Example usage for edu.stanford.nlp.classify RVFDataset RVFDataset

Introduction

In this page you can find the example usage for edu.stanford.nlp.classify RVFDataset RVFDataset.

Prototype

public RVFDataset() 

Source Link

Usage

From source file:gr.aueb.cs.nlp.wordtagger.classifier.MaxEntClassifier.java

License:Open Source License

@Override
public void train(List<Word> trainSet) {
    RVFDataset<String, String> ds = new RVFDataset<>();
    ds.addAll(WordSet.toStanfordSet(trainSet));
    //unfortunately couldn't find hot to retrain;
    this.classifier = classifier == null ? classifierFactory.trainClassifier(ds) : classifier;
}

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From source file:gr.aueb.cs.nlp.wordtagger.classifier.SVMClassifier.java

License:Open Source License

@Override
public void train(List<Word> trainSet) {
    RVFDataset<String, String> ds = new RVFDataset<>();
    ds.addAll(WordSet.toStanfordSet(trainSet));
    //classifierFactory.heldOutSetC(ds, 0.1, new MultiClassAccuracyStats<String>(1), new GoldenSectionLineSearch(true));
    //classifierFactory.crossValidateSetC(ds, 2, new MultiClassAccuracyStats<String>(1), new GoldenSectionLineSearch(true));
    this.classifier = classifier == null ? classifierFactory.trainClassifierBasic(ds) : classifier;
}

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From source file:gr.aueb.cs.nlp.wordtagger.classifier.SVMWindows64Factory.java

License:Open Source License

/**
 * Builds a sigmoid model to turn the classifier outputs into probabilities.
 *//*from w  w w .  ja va  2  s.c  o m*/
private LinearClassifier<L, L> fitSigmoid(SVMLightClassifier<L, F> classifier, GeneralDataset<L, F> dataset) {
    RVFDataset<L, L> plattDataset = new RVFDataset<L, L>();
    for (int i = 0; i < dataset.size(); i++) {
        RVFDatum<L, F> d = dataset.getRVFDatum(i);
        Counter<L> scores = classifier.scoresOf((Datum<L, F>) d);
        scores.incrementCount(null);
        plattDataset.add(new RVFDatum<L, L>(scores, d.label()));
    }
    LinearClassifierFactory<L, L> factory = new LinearClassifierFactory<L, L>();
    factory.setPrior(new LogPrior(LogPrior.LogPriorType.NULL));
    return factory.trainClassifier(plattDataset);
}

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